Jeff Braga

Reinforcement Learning · 2022

A researcher in the Science corpus: 1 paper; trusts 5 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Jeff Braga trusts

Their strongest outbound trust, strongest first, inferred from their citations.

  1. Santiago Ontan'on (in Artificial Intelligence)
  2. Shengyi Huang (in Artificial Intelligence)
  3. Tom Erez (in Control and Systems Engineering)
  4. Yuval Tassa (in Control and Systems Engineering)
  5. John Schulman (in Reinforcement Learning)

Papers from Jeff Braga's perspective

Ordered by how strongly the researchers Jeff Braga trusts endorse each paper. Same corpus, a different order for every researcher.

  1. Proximal Policy Optimization Algorithms (arXiv.org)
  2. Continuous control with deep reinforcement learning (International Conference on Learning Representations)
  3. MuJoCo: A physics engine for model-based control
  4. Playing Atari with Deep Reinforcement Learning (arXiv.org)
  5. The Arcade Learning Environment: An Evaluation Platform for General Agents
  6. OpenAI Gym
  7. Soft Actor-Critic: Off-Policy Maximum Entropy Deep Reinforcement Learning with a Stochastic Actor (International Conference on Machine Learning)
  8. Exploration by Random Network Distillation
  9. Addressing Function Approximation Error in Actor-Critic Methods
  10. Soft Actor-Critic Algorithms and Applications

Their papers